code: def test_inq_affine_recomputation(
      seed,
      base_axis,
      weight_shape,
      num_bits,
      bias,
      inq_iterations,
      selection_algorithm,
      func_seed,
      ctx,
      func_name,
  ):
      from nbla_test_utils import recomputation_test
  
      rng = np.random.RandomState(seed)
      # Input
      inputs = [rng.randn(2, 3, 4).astype(np.float32)]
      # Weights
      inputs += [rng.randn(*weight_shape).astype(np.float32)]
      # Indices
      inputs += [np.random.randint(2, size=weight_shape)]
      # Bias
      if bias:
          inputs += [rng.randn(*weight_shape[1:]).astype(np.float32)]
      else:
          inputs += [None]
  
      func_args = [
          base_axis,
          num_bits,
          inq_iterations,
          selection_algorithm,
          func_seed,
      ]
  
      vinputs = []
      for i in inputs:
          if i is None:
              vinputs.append(None)
          else:
              vinputs.append(nn.Variable.from_numpy_array(i))
  
      recomputation_test(
          rng=rng,
          func=F.inq_affine,
          vinputs=vinputs,
          func_args=func_args,
          func_kwargs={},
          ctx=ctx,
      )
  
file_path: nnabla/python/test/function/test_inq_affine.py
imports: import pytest
  import numpy
  import nnabla
  import nnabla.functions
  from nbla_test_utils import list_context
label_desc: Use image node_id 5 for calling a global function with example usage: test_inq_affine_recomputation(seed, base_axis, weight_shape, num_bits, bias, inq_iterations, selection_algorithm, func_seed, ctx, func_name) without return types